Large model API platform

Zilliz is an enterprise-grade vector database and Milvus hosting platform aimed at AI application developers, data engineering teams, and enterprise retrieval teams. Its value is not to make all the work for the user at once, but to provide actionable assistance around building vector retrieval, RAG, and large-scale similarity search services: users can create vector libraries, write data, run retrieval, expand capacity, and then complete the subsequent processing based on their own business judgment. When choosing such tools, you need to pay attention to data permissions, index design, and query costs, especially when it comes to accounts, customer information, contracts, courses, audio, video, or code output, all of which should be manually reviewed. Its visibility capabilities include Vector Lakebase, Milvus, real-time vector search, and lake-scale discovery, making it more suitable for enterprise AI retrieval infrastructure.

Xpoz MCP is a social data API for AI Agents, primarily aimed at marketing teams, intelligence analytics, and AI Agent developers, providing data interfaces for brand monitoring, social listening, and lead analysis. It's for people who already have clear tasks, assets, or business processes, bringing together social data APIs, brand monitoring, and competitive intelligence into easier workflows. When using it, you need to focus on platform policies, data authorization, and privacy compliance, especially when it involves customer data, learning content, audio and video materials, business data, or public release, you should first confirm authorization and manual review. Overall, Xpoz MCP is suitable as an auxiliary tool for providing data interfaces for brand monitoring, social listening, and lead analysis, rather than a substitute for professional final judgment.

XCrawl is an AI web scraping and structured data extraction API aimed at developers, data teams, and AI app builders for scraping web pages and outputting structured JSON, Markdown, or search data. It's for those who already have a clear task, footage, or business process that brings together structured extraction, built-in agents, and AI-ready web scraping into a more actionable workflow. When using it, you need to focus on website permissions, rate limiting, and data compliance, especially when it comes to customer information, learning content, audio and video materials, business data, or public publishing. Overall, XCrawl is suitable as an aid for scraping web pages and outputting structured JSON, Markdown, or search data, rather than a substitute for the final judgment of professionals.

WebscrapeAI is a no-code web data collection automation tool aimed at operators, data teams, and researchers to automatically collect web data and organize structured results. It's better for people who already have clear assets, scripts, customer communications, or business processes that centralize no-code ingestion, structured extraction, and automation tasks into a one-to-one workflow that's easier to execute. When using it, you need to pay attention to website permissions, anti-crawling rules, and data compliance, especially when it comes to customer information, human voices, image materials, web page data, or published content, you should first confirm authorization and manual review. Overall, WebscrapeAI is suitable as an auxiliary tool for automatically collecting web page data and organizing structured results, rather than a complete replacement for the final judgment of editors, operations, R&D, or management.

WaterCrawl is a web scraping framework for LLMs, primarily aimed at developers, data teams, and AI application builders, to convert web content into data suitable for large models. It is more suitable for people who already have clear materials, scripts, customer communications, or business processes, centralizing web scraping, structured output, and large model data preparation into a more performable workflow. When using it, you need to pay attention to crawl permissions, rate limiting, and data compliance, especially when it comes to customer information, character voices, image materials, web page data, or published content. Overall, WaterCrawl is suitable as an auxiliary tool for converting web content into data suitable for large models, rather than completely replacing the final judgment of editors, operations, R&D, or managers.

VoiceAIWrapper is an AI API and developer platform for teams and creators who need a practical way to generate, organize, convert, or review work before it moves into a final production flow. It is best used with clear source material, a defined output goal, and a human review step for accuracy, rights, privacy, and publishing quality.

VideoSDK is an AI API and developer platform for teams and creators who need a practical way to generate, organize, convert, or review work before it moves into a final production flow. It is best used with clear source material, a defined output goal, and a human review step for accuracy, rights, privacy, and publishing quality.

Veryfi is an AI API and developer platform for teams and creators who need a practical way to generate, organize, convert, or review work before it moves into a final production flow. It is best used with clear source material, a defined output goal, and a human review step for accuracy, rights, privacy, and publishing quality.

VerbaGPT is an AI API and developer platform for teams and creators who need a practical way to generate, organize, convert, or review work before it moves into a final production flow. It is best used with clear source material, a defined output goal, and a human review step for accuracy, rights, privacy, and publishing quality.

Upstage AI is an AI workflow tool for teams that need to create, organize, convert, or review task-specific material before final use. It should be used with clear source material, a defined output goal, and human review for accuracy, rights, privacy, and publishing quality.

Together AI is an AI workflow tool for teams that need to create, organize, convert, or review task-specific material before final use. It should be used with clear source material, a defined output goal, and human review for accuracy, rights, privacy, and publishing quality.

TiDB Cloud is an AI workflow tool for creating, organizing, converting, or reviewing task-specific material before final use. It should be used with clear source material, a defined output goal, and human review for accuracy, rights, privacy, and publishing quality.

Thunder Compute is an AI tool for users who need a clearer way to handle focused digital work. It can support creation, automation, analysis, learning, media production, development, research, customer operations, or document workflows depending on the product scope. Start with a small low-risk task, compare the result with your own standards, and keep human review for facts, permissions, privacy, brand voice, safety, and final delivery.

T-Rex Label is a practical AI tool for teams and individual users who need a clearer way to handle focused digital tasks. It can support content work, document handling, automation, learning, communication, media production, research, or customer workflows depending on the product scope. Users should start with a small low-risk task, compare the output with their own standards, and keep human review for facts, permissions, privacy, brand voice, and final delivery.

Squirro is an AI API and data platform suitable for developers, data teams, AI product teams and business analysts to use when improving productivity, reducing costs, and providing safe, private and accurate AI-driven enterprise intelligence. Its focus is on organizing data, models or business contexts into query-friendly and accessible workflows. Current visible capabilities include AI-driven enterprise intelligence that improves productivity, reduces costs, and is secure, private and accurate. It is more suitable for users with clear needs and budgets. Plans, quotas and team collaboration requirements should be confirmed before using. Before accessing, you must confirm the call cost, data authorization, authority scope and error handling method. If you plan to use it for a long time, it is recommended to use a real but low-risk task to test input preparation, output stability, manual review costs and authority boundaries before deciding whether to include it in a fixed process.

SQLAI.ai is an AI API and data platform suitable for developers, data teams, AI product teams and business analysts to use when generating and optimizing SQL queries. Its focus is to organize data, models or business contexts into query-friendly and accessible workflows. Current visible capabilities include 7-day free trial, generation of SQL queries, and optimization of SQL queries. It provides free entry or trial credits, which is suitable for verifying a small task before deciding whether to pay. Before accessing, you must confirm the call cost, data authorization, authority scope and error handling method. If you plan to use it for a long time, it is recommended to use a real but low-risk task to test input preparation, output stability, manual review costs and authority boundaries before deciding whether to include it in a fixed process.

Spice AI is an AI API and data platform suitable for developers, data teams, AI product teams, and business analysts to use when combining data and artificial intelligence building blocks, SQL query federation and acceleration. Its focus is on organizing data, models or business contexts into query-friendly and accessible workflows. Current visible capabilities include composable data and artificial intelligence building modules, SQL query federation and acceleration. It is more suitable for users with clear needs and budgets. Plans, quotas and team collaboration requirements should be confirmed before using. Before accessing, you must confirm the call cost, data authorization, authority scope and error handling method. If you plan to use it for a long time, it is recommended to use a real but low-risk task to test input preparation, output stability, manual review costs and authority boundaries before deciding whether to include it in a fixed process.

Spectate is an AI API and data platform suitable for developers, data teams, AI product teams and business analysts to use when using 5 monitors, full-stack monitoring, and AI-driven event management. Its focus is to organize data, models or business contexts into query-friendly and accessible workflows. Currently, visible capabilities include 5 monitors, servers, and 1 status page for free, full-stack monitoring. It provides free entry or trial credits, which is suitable for verifying a small task before deciding whether to pay. Before accessing, you must confirm the call cost, data authorization, authority scope and error handling method. If you plan to use it for a long time, it is recommended to use a real but low-risk task to test input preparation, output stability, manual review costs and authority boundaries before deciding whether to include it in a fixed process.

Sparkco AI Spreadsheet Agent is an AI API and data platform suitable for developers, data teams, AI product teams and business analysts to use when using natural language formulas and automatic data synchronization. Its focus is to organize data, models or business contexts into query-friendly and accessible workflows. Currently visible capabilities include permanent free (3 workbooks, 5 data sources), natural language formulas, and automatic data synchronization. It provides free entry or trial credits, which is suitable for verifying a small task before deciding whether to pay. Before accessing, you must confirm the call cost, data authorization, authority scope and error handling method. If you plan to use it for a long time, it is recommended to use a real but low-risk task to test input preparation, output stability, manual review costs and authority boundaries before deciding whether to include it in a fixed process.

SoLike is an AI API and automation platform for developers, data teams, AI product teams, and automation engineers to respond with human-like AI responses and enhance cross-platform engagement. It focuses on encapsulating models, data, or automation capabilities into accessible workflows, with current visible capabilities including free testing, human-like AI responses, and enhanced cross-platform engagement. It offers a free entry or trial credit, which is good for verifying a small task before deciding whether to pay or not. Before accessing, check the call cost, rate limit, data authorization, and error handling method. If you are going to use it for a long time, it is recommended to test input preparation, output stability, manual review costs, and permission boundaries with a real but low-risk task before deciding whether to include a fixed process.

Softgen.ai is an AI API and automation platform suitable for developers, data teams, AI product teams and automation engineers to use when building AI web application builders, requiring no coding, and building full-stack applications. Its focus is on encapsulating models, data or automation capabilities into accessible workflows. Currently visible capabilities include free 100K tokens, AI web application builders, and no coding required. It provides free entry or trial credits, which is suitable for verifying a small task before deciding whether to pay. Before accessing, you must confirm the call cost, rate limit, data authorization and error handling method. If you plan to use it for a long time, it is recommended to use a real but low-risk task to test input preparation, output stability, manual review costs and authority boundaries before deciding whether to include it in a fixed process.

Skyvern is an AI API and automation platform for developers, data teams, AI product teams, and automation engineers for AI browser automation, computer vision for any web page, CAPTCHA support, and two-factor authentication. Its focus is on encapsulating models, web pages, or browser capabilities into interfaces that developers can call, and currently visible capabilities include open source (free), AI browser automation, and computer vision adapted to any web page. It offers a free entry or trial credit, which is good for verifying a small task before deciding whether to pay or not. Before accessing, check the call cost, rate limit, data authorization, target site rules, and error handling methods. If you are going to use it for a long time, it is recommended to test input preparation, output stability, manual review costs, and permission boundaries with a real but low-risk task before deciding whether to include a fixed process.

Skrape.ai is an AI API and automation platform for developers, data teams, AI product teams, and automation engineers working with AI-powered web crawler APIs, structured data for AI, and RAG systems. Its focus is on encapsulating models, web pages, or browser capabilities into interfaces that developers can call, and currently visibility includes 50 request-free, AI-powered web crawler APIs for AI. It offers a free entry or trial credit, which is good for verifying a small task before deciding whether to pay or not. Before accessing, check the call cost, rate limit, data authorization, target site rules, and error handling methods. If you are going to use it for a long time, it is recommended to test input preparation, output stability, manual review costs, and permission boundaries with a real but low-risk task before deciding whether to include a fixed process.

SiliconFlow is an AI API and automation platform for developers, data teams, AI product teams, and automation engineers to deploy LLMs and multimodal models, fine-tune models. It focuses on encapsulating models, web pages, or browser capabilities into interfaces that developers can call, and currently visible capabilities include $1 free credit, deploying LLMs and multimodal models, and fine-tuning models. It offers a free entry or trial credit, which is good for verifying a small task before deciding whether to pay or not. Before accessing, check the call cost, rate limit, data authorization, target site rules, and error handling methods. If you are going to use it for a long time, it is recommended to test input preparation, output stability, manual review costs, and permission boundaries with a real but low-risk task before deciding whether to include a fixed process.

Scrapingdog is a web scraping and search data API for developers, data collection teams, and businesses that need search results or map data when calling APIs such as Google SERPs, AI Overview, Maps, News, and more to extract structured data. It focuses on encapsulating proxies, headless browsers, and anti-crawling processing into a unified API, with key capabilities including web scraping APIs, including Google SERPs, AI Mode, AI Overview, and Maps APIs, and support for structured JSON data extraction. It's better suited for teams with clear budget and process needs. Before use, it should be noted that the frequency of data collection should be controlled, the platform rules should be followed, and the scope of service use should be confirmed. If you plan to adopt it for a long time, it is recommended to test input lead time, output availability, manual review costs, and permission boundaries with real samples before deciding whether to put it into a fixed process.

ScrapeGraphAI is a web data scraping API for the AI era for developers, data teams, and product teams that need structured web data to extract structured data from websites, reducing agents, selectors, and maintenance efforts. It focuses on streamlining the web scraping process into a callable, maintainable data interface, with key capabilities such as providing ScrapeGraphAI V2, eliminating the need for proxies and selectors, API documentation, and startup resources. It's better suited for teams with clear budget and process needs. Note Before Use: Adhere to the target website's terms, robots rules, and data usage authorization before scraping. If you plan to adopt it for a long time, it is recommended to test input lead time, output availability, manual review costs, and permission boundaries with real samples before deciding whether to put it into a fixed process.

Runware is a multi-model generative AI API platform for developers, AI product teams, and enterprises that need unified access to multiple types of generative models when calling images, videos, audio, LLMs, 3D, and more through a single API. It focuses on integrating multi-model capabilities into products in a low-cost, on-demand scaling manner, including support for image, video, audio, LLM, and 3D, providing free test credits, and emphasizing low cost and instant scale. It offers free entry or trial credits, which are suitable for verifying results with small tasks first. Note before use: The output quality, copyright boundaries, and fee structure of different models need to be tested by product scenario. If you plan to adopt it for a long time, it is recommended to test input lead time, output availability, manual review costs, and permission boundaries with real samples before deciding whether to put it into a fixed process.

Rube is an AI-oriented, cross-app action tool for developers, automation teams, and users who want to connect AI to everyday tools when it comes to letting AI perform actions through apps like Gmail, Slack, Calendar, social media, and more. It focuses on connecting application certification, tool selection, and cross-app actions to AI use, with key capabilities including being launched by Composio, supporting over 600 apps, and offering Marketplace, Recipes, and Pricing. It offers free entry or trial credits, which are suitable for verifying results with small tasks first. Before use, you should set permissions, confirmation steps, and audit records before performing actions such as email, calendar, and social posting. If you plan to adopt it for a long time, it is recommended to test input lead time, output availability, manual review costs, and permission boundaries with real samples before deciding whether to put it into a fixed process.

Raindrop AI is an AI workflow tool for teams that need to create, organize, convert, or review task-specific material before final use. It should be used with clear source material, a defined output goal, and human review for accuracy, rights, privacy, and publishing quality.

Ragie is an AI workflow tool for teams that need to create, organize, convert, or review task-specific material before final use. It should be used with clear source material, a defined output goal, and human review for accuracy, rights, privacy, and publishing quality.

PredictOPs is an AI workflow tool for teams that need to create, organize, convert, or review task-specific material before final use. It should be used with clear source material, a defined output goal, and human review for accuracy, rights, privacy, and publishing quality.

Predictive Equations is an AI workflow tool for teams that need to create, organize, convert, or review task-specific material before final use. It should be used with clear source material, a defined output goal, and human review for accuracy, rights, privacy, and publishing quality.

Plat.AI is an AI workflow tool for teams that need to create, organize, convert, or review task-specific material before final use. It should be used with clear source material, a defined output goal, and human review for accuracy, rights, privacy, and publishing quality.

Pinecone is an AI workflow tool for teams that need to create, organize, convert, or review task-specific material before final use. It should be used with clear source material, a defined output goal, and human review for accuracy, rights, privacy, and publishing quality.

Phare is an AI workflow tool for teams that need to create, organize, convert, or review task-specific material before final use. It should be used with clear source material, a defined output goal, and human review for accuracy, rights, privacy, and publishing quality.

Pangeanic is an AI data annotation, model evaluation and multilingual data platform. It is mainly used to provide multilingual training data, model alignment, LLM evaluation, data annotation management and enterprise-level AI deployment support. It is suitable for AI teams, government agencies, enterprise R & D, language technology teams and organizations that require multilingual data operations. Common uses include building multilingual model training data, evaluating LLM output quality and security, and deploying linguistic AI systems for enterprises or governments. When using it, it should be noted that data operation projects usually require clear labeling specifications, privacy processing and quality sampling mechanisms, and cannot rely solely on automated processes. For corporate and project-based procurement, it is usually necessary to contact the team to confirm the scope and quotation. It is recommended to use one or two low-risk tasks to test input materials, output quality, manual modification amount and final adoption ratio before deciding whether to put them into a fixed process.

Novita AI is an AI model API and proxy cloud platform that is mainly used to access multiple models, proxy sandboxes and GPU resources through one API. It is suitable for developers, entrepreneurial teams, AI application teams and platform engineers. It can provide multi-model API access, launch agent sandboxes and GPU instances, and is also suitable for quickly building AI applications and prototypes. Pay attention when using it, and evaluate model costs, current limiting, data security and fault coverage before going online. It is recommended that one or two low-risk tasks be used to test input materials, output quality, manual modifications, and final adoption ratios before deciding whether to put them into a fixed process and document whether they are suitable for long-term use and team review.

LlamaIndex is an AI data framework and document parsing platform developed for AI Agents and knowledge assistants, providing document OCR, parsing, data access, and workflow capabilities to help developers connect unstructured data to large model applications. It's suitable for AI engineers, data teams, enterprise knowledge base projects, and development teams that need to work with complex documents. Before use, it is recommended to conduct small-scale testing with real materials or real processes, focusing on observing output quality, review costs, payment boundaries, data permissions, and whether the team can establish a stable manual review process. Before handling formal business, it should also be judged based on material authorization, privacy requirements, and manual review standards, and avoid using automatic results directly for external release or key decisions. If used in team, client, or teaching scenarios, the source of information, the responsibility for reviewing the results, and the scope of external use should also be clearly entered first.

Latitude is an observability platform for AI Agents that helps teams monitor, evaluate, and improve agent performance, and provides support around prompting, evaluation runs, and engineering processes. It's suitable for AI engineering teams, product teams, platform teams, and organizations that need to maintain agents for a long time. Before use, it is recommended to conduct a small-scale test with real materials, focusing on observing the output quality, review cost, payment boundaries, data permissions, and whether the team can establish a stable manual review process. Before handling formal business, it should also be judged based on material authorization, privacy requirements, and manual review standards, and avoid using automatic results directly for external release or key decisions. If you are using it for a team, client, or teaching scenario, it is recommended to first confirm the source of the input material, the responsibility for reviewing the results, and the scope of external use.

LangWatch is a test, evaluation, and observability platform for AI Agent and LLM applications, supporting simulated user testing, regression protection, debugging, monitoring, and evaluation. It's suitable for AI engineering teams, product teams, platform teams, and organizations that need to continuously verify agent quality. Before use, it is recommended to conduct a small-scale test with real materials, focusing on observing the output quality, review cost, payment boundaries, data permissions, and whether the team can establish a stable manual review process. Before handling formal business, it should also be judged based on material authorization, privacy requirements, and manual review standards, and avoid using automatic results directly for external release or key decisions. If you are using it for a team, client, or teaching scenario, it is recommended to first confirm the source of the input material, the responsibility for reviewing the results, and the scope of external use.

Langtail is a prompt management platform for product teams that helps teams build, test, and deploy AI prompts, with LLM testing, logging, AI firewalls, and prompt collaboration capabilities. It's suitable for AI product managers, developers, LLM application teams, and those who need to manage prompt versions. Before use, it is recommended to conduct a small-scale test with real materials, focusing on observing the output quality, review cost, payment boundaries, data permissions, and whether the team can establish a stable manual review process. Before handling formal business, it should also be judged based on material authorization, privacy requirements, and manual review standards, and avoid using automatic results directly for external release or key decisions. If you are using it for a team, client, or teaching scenario, it is recommended to first confirm the source of the input material, the responsibility for reviewing the results, and the scope of external use.

Landing AI is a vision AI platform that helps teams build AI-powered applications focused on creating, deploying, and managing computer vision models. It is suitable for manufacturing, quality inspection, industrial vision, retail inspection, and teams that need to implement image recognition capabilities into business processes. The platform offers a monthly points plan. Before use, you should prepare the annotation data, validation set, deployment environment, and service acceptance indicators, and check the model for false positives, missed checks, and data deviations in real-world scenarios. Before use, it is recommended to conduct a small-scale test with real materials, focusing on observing the output quality, review cost, payment boundaries, data permissions, and whether the team can establish a stable manual review process. Before handling formal business, it should also be judged by team processes, material authorization, and manual review criteria to avoid using automated results directly for external release or key decisions.

LAION is a Large-scale Artificial Intelligence Open Network, a non-profit open AI organization dedicated to making machine learning resources, including datasets, tools, and model-related projects, available to the public. It is suitable for researchers, machine learning engineers, open-source communities, educational institutions, and those who need to learn about open data resources. LAION itself is not a single application, but an open source network. Before using their data or models, they should confirm compliance with licenses, data sources, risk of bias, ethical restrictions, and downstream tasks. Before use, it is recommended to conduct a small-scale test with real materials, focusing on observing the output quality, review cost, payment boundaries, data permissions, and whether the team can establish a stable manual review process.

Label Studio is an open-source data annotation and AI evaluation platform that supports a wide range of data types, including computer vision, document AI, NLP, audio transcription, agent trajectory, LLM evaluation, RLHF, and more. It's suitable for machine learning teams, data annotation teams, researchers, and businesses that need to build training or evaluation datasets. The platform offers open-source versions and commercial solutions. When using it, you should design annotation specifications, quality inspection processes, permission management, and data compliance policies to avoid low-quality annotations affecting model performance. Before use, it is recommended to conduct a small-scale test with real materials, focusing on observing the output quality, review cost, payment boundaries, data permissions, and whether the team can establish a stable manual review process. Before handling formal business, it should also be judged by team processes, material authorization, and manual review criteria to avoid using automated results directly for external release or key decisions.

Klu is a development platform for LLM application teams, covering prompt design, application deployment, data integration, evaluation, collaborative prompt engineering, and model fine-tuning. It is suitable for AI product teams, developers, machine learning teams, and internal automation projects to advance large language model applications from experimentation to monitorable, evaluative production environments. The platform offers paid plans. Before use, you should confirm the data source, model selection, evaluation metrics, privacy boundaries, and team collaboration process to avoid judging the effect based on a single presentation. Before use, it is recommended to conduct a small-scale test with real materials, focusing on observing the output quality, review cost, payment boundaries, data permissions, and whether the team can establish a stable manual review process.

Kie AI is an AI API platform for developers and product teams, providing access capabilities to models such as chat, images, videos, and music, with an emphasis on free API keys, stable performance, scalable calls, and real-time stream output. It's suitable for AI application development, content generation products, multimodal feature integration, and teams that require a unified model entrance. Before accessing, you need to evaluate the response quality, latency, quota, cost, content security policy, generation material authorization, and failure retry mechanism to avoid directly connecting interface capabilities to formal services. Before use, it is recommended to conduct a small-scale test with real materials, focusing on observing the output quality, review cost, payment boundaries, data permissions, and whether the team can establish a stable manual review process.

Kapsul is a data infrastructure platform that provides Storage as a Software with a focus on programmable storage, adaptive privacy, and managing data by context. It is suitable for developers, AI application teams, and products that require fine-grained control over data storage, permissions, and costs to build a more flexible data layer. The platform offers free API requests and per-GB billing plans. Evaluate data types, permission models, encryption requirements, latency, cost, and compliance responsibilities before onboarding. It's more suitable for users with clear goals, input materials, and boundaries, and small-scale testing can help you determine whether the results are worth going into the formal process faster. Before use, you should also use your own data sources, team processes, and review criteria to avoid direct automatic results into official release, submission, or business decisions.

The Jobo API is a job data infrastructure for recruiting, job searching, and career platforms, offering capabilities related to extensive job listings, ATS platform coverage, data synchronization, and automated applications. It is suitable for recruiting technology products, job search tools, career service platforms, and internal talent systems to access job data, sync to business systems, and build job search related functions. The current page is more about API and platform services than individual job seeker tools. Before accessing, data authorization, application automation boundaries, platform terms, and user privacy need to be evaluated. If you want to include it in a long-term process, it is recommended to use a small task to verify the output quality, quota consumption, authorization boundaries, and manual modification costs before deciding whether to expand the scope of use.